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Log-Laplace distribution

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Log-Laplace distribution
Probability density functionProbability density functions for Log-Laplace distributions with varying parameters μ {\displaystyle \mu } and b {\displaystyle b} .
Cumulative distribution functionCumulative distribution functions for Log-Laplace distributions with varying parameters μ {\displaystyle \mu } and b {\displaystyle b} .

In probability theory and statistics, the log-Laplace distribution is the probability distribution of a random variable whose logarithm has a Laplace distribution. If X has a Laplace distribution with parameters μ and b, then Y = e has a log-Laplace distribution. The distributional properties can be derived from the Laplace distribution.

Characterization

A random variable has a log-Laplace(μ, b) distribution if its probability density function is:

f ( x | μ , b ) = 1 2 b x exp ( | ln x μ | b ) {\displaystyle f(x|\mu ,b)={\frac {1}{2bx}}\exp \left(-{\frac {|\ln x-\mu |}{b}}\right)}

The cumulative distribution function for Y when y > 0, is

F ( y ) = 0.5 [ 1 + sgn ( ln ( y ) μ ) ( 1 exp ( | ln ( y ) μ | / b ) ) ] . {\displaystyle F(y)=0.5\,.}

Generalization

Versions of the log-Laplace distribution based on an asymmetric Laplace distribution also exist. Depending on the parameters, including asymmetry, the log-Laplace may or may not have a finite mean and a finite variance.

References

  1. Lindsey, J.K. (2004). Statistical analysis of stochastic processes in time. Cambridge University Press. p. 33. ISBN 978-0-521-83741-5.
  2. ^ Kozubowski, T.J. & Podgorski, K. "A Log-Laplace Growth Rate Model" (PDF). University of Nevada-Reno. p. 4. Archived from the original (PDF) on 2012-04-15. Retrieved 2011-10-21.
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